Research On Resource Management Of Distributed UAV Radar System

In the face of the increasingly complex electromagnetic environment and diverse tasks,single UAV radar has been unable to meet the increasingly high performance requirements of the system.Distributed UAV radar system has higher detection,tracking and positioning ability,as well as the stronger anti-stealth and anti-jamming ability.The resources of distributed UAV radar system is limited,how to allocate the resources of radar system effectively and reasonably,under the premise of meeting the requirements of the system,is of great significance to further improve the utilization of system resources.Based on the acquired prior informationof environment,target,noise and clutter by situation sharing and cooperative sensing of distributed UAV radar system,?establish the resources optimization model under different constraint conditions,improve and design the appropriate optimization algorithms for solving optimization problems,verify the feasibility of the algorithms through simulations? as the basic research ideas,this paper then carry out the basic research on the related resources of UAV radar sestem from waveform design,target positioning based power distribution,subset selection based system reconfiguration three aspects.During the study,the suitable fuzzy programming model and fuzzy optimization algorithm are used to model,solve and analyze some objective functions with fuzzy radar parameters.The main work and innovations of this paper are as follows:1.Based on the linear frequency modulation(LFM)signal,the waveform design of UAV radar system in non-Gauss clutter is studied.Firstly,the optimization model based maximizing the signal-to-clutter-plus-noise ratio(SCNR)under the bandwidth and emission energy constraints is constructed,then the optimal waveforms are obtained by using the nonlinear programming genetic algorithm(NPGA);finally,the simulation results show that NPGA has faster convergence speed when compared with interior point method;and under the same constraints,the performance of SCNR of the optimized waveforms are better when compared with the frequency spread LFM signal.2.The power allocation problem based on target location is studied.On the one hand,the problem of minimizing the transmission power of the system under the given positioning error constraint is studied;on the other hand,the problem of minimizing the positioning error under the total system power constraint is studied;this paper based on appropriate improvements to the existing power allocation strategy,the goal of minimizing of transmit power or the target location error is realized.3.Considering the fuzziness of the target radar cross section(RCS),firstly,an allocation strategy to minimize the total power of the system based on fuzzy chance constrained programming(FCCP)is constructed;then the optimal solution of the FCCP problem is obtained by using the hybrid intelligent algorithm;finally,a series of simulation results validated that the FCCP model has better stability and higher reference value when studying the optimization problem with fuzzy variables compared the case without considering the fuzziness of the variables.4.The subset selection problem of UAV radar system is studied.On the one hand,the problem of choosing the minimal number of radars to achieve the given target localization error is studied,at the same time,considering the fuzziness of radar cost factors,a fuzzy linear programming(FLP)based selection strategy of minimal set is constructed;on the other hand,the problem of choosing a subset of given number of radars to minimize the target positioning error is studied.The simulation results verified the effectiveness of the two kinds of selection strategies,and drew a conclusion that the FLP based minimal subset selection strategy has better robustness when the prior knowledge of fuzzy variable was poorly understood.